Machine Learning Based Energy Efficient Cluster Head Selection Algorithms for Lifetime Enhancement In Wireless Sensor Network

Abstract

The development of wireless communications has resulted in a significant increase in the amount of interest shown in the study of Wireless Sensor Networks (WSN). A wireless sensor network (WSN) is made up of a large number of sensor nodes that are all digitally connected to one another. The sensor nodes are in charge of perceiving their surroundings, processing the data they collect, and maintaining communication with other sensor nodes. These sensor nodes collaborate with one another in an ordered manner to accomplish a common goal. All of the actions that need to be completed are totally dependent on the amount of energy or battery that the sensor nodes have. It is not possible to replace or recharge the batteries of the sensors because the WSN is primarily used for responding to urgent situations. WSNs have limited access to energy sources; as a result, it is imperative that the power they do have be utilized effectively. The amount of energy that a network uses is inversely proportional to the amount of time it will remain operational. newline